The present invention relates to the field of business rule management and, more particularly, to utilizing a dynamic data source to affect business rule management.
Business rules which can aid in organizing, implementing, and achieving business objectives can range from simple to highly complex. Business rules are traditionally managed by business rules management systems (BRMS). These management systems often require a manual update and approval by multiple business users before a business rule can be modified. This can result in significant time delays which can drive up decision and implementation costs. For example, if there is a change to raw material prices, a manufacturer must manually adjust their product pricing to compensate for the change in raw material price. Currently there is no tool or methodology to accommodate the dynamic nature of the business environment.
Further, due to the vast quantities of data sources in the business environment, business analysts can be overwhelmed, resorting to utilizing only a few key resources. For example, many Big Data sources which can vary from terabytes to petabytes of information are too cumbersome for human management and/or consumption. Additionally, disparate organization of sources creates another hurdle which business analysts must overcome before utilizing critical information from these sources. For example, important Internet articles, news feeds, and social network information can go unleveraged due to the loosely organized relationships they have with each other. That is, current methodologies for organizing and/or analyzing disparate data sources can be time and cost prohibitive.